Human gait analysis and assessment involves challenging issues due to the highly flexible structure and self-occlusion of the human body. These issues mandate using complicated processes for the measurement and analysis. Typically, gait analysis is performed in a gait laboratory that uses a combination of technologies to evaluate the biomechanics of gait: a marker-based motion capture system, force plates, an electromyography system, and a pressure sensitive electronic walkway. The systems used in a gait laboratory provide accurate descriptions and models of gait. However, these expensive systems must be installed in appropriate rooms and can only be operated by specially trained personnel in a clinical setting. However, a clinical visit is not only costly, but also ineffective for many applications because 1) the clinical walkway is not representative of the complex environment within which a subject must function; and 2) the symptoms of many diseases can vary greatly from time-to-time.
Among the most widely used and studied techniques for gait analysis and assessment utilize wearable sensors such as those based on accelerometers and gyroscopes. Many wearable systems have demonstrated accuracy and precision, but suffer from limitations such as short battery life, the need to download the data or introduce additional hardware for wireless data collection, and the inconvenience of both a wearable device and having to remember to wear a device. For these reasons, wearable devices are currently inadequate for long-term, in-home, unobtrusive monitoring.
Gait characteristics have been linked with a variety of medical conditions in clinical research. A change in the gait profile over time may indicate a disease state change or a person is at risk of falling. Hence, monitoring walking patterns on a daily basis using smart-home technologies, such as camera monitors and/or walking-sensors, can provide essential information on the change of functional status of a subject.
Thus, continuous gait assessment would provide clear advantages over the clinic-based tests, especially for seniors living in nursing homes, while monitoring their regular day-to-day activities, as walking is one of the most natural physical activities and can be conveniently and easily accommodated into an older adult's routine. Such a monitoring system when combined with advanced algorithms to detect subtle gait changes can potentially be used to identify diagnostic measures that are predictors of fall-prone elderly or disease status change so that effective interventions can be made in a timely manner to prevent or reduce severe health outcomes.
There is, therefore, a clear need for an inexpensive, unobtrusive and easy-to-use system, which allows continuous and quantitative analysis of gait patterns outside the lab.